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FastAPI is a great web framework for creating web APIs with Python; It offers us multiple features with which it is possible to create modular, well-structured, scalable APIs with many options such as validations, formats, typing, among others. When you install FastAPI, two very important modules are installed: Pydantic that allows the creation of models for data validation. Starlette, which is a lightweight ASGI tooltip, used to create asynchronous (or synchronous) web services in Python. With these packages, we have the basics to create APIs, but we can easily extend a FastAPI project with other modules to provide the application with more features, such as the database, template engines, among others. FastAPI is a high-performance, easy-to-learn, start-up framework; It is ideal for creating all kinds of sites that not only consist of APIs, but we can install a template manager to return complete web pages. This book is mostly practical, we will learn the basics of FastAPI, knowing its main features based on a small application that we will extend chapter after chapter and whose content you can see below: Chapter 1: We present some essential commands to develop in FastApi , we will prepare the environment and we will give an introduction to the framework . Chapter 2: One of the main factors in FastApi is the creation of resources for the API through functions, in this section we will deal with the basics of this, introducing routing between multiple files as well as the different options for the arguments and parameters of these routes. Chapter 3: In this section, learn how to handle HTTP status codes from API methods and also handle errors/exceptions from API methods. Chapter 4: In this section we will see how to create sample data to use from the automatic documentation that FastAPI offers for each of the API methods. Chapter 5: In this chapter we will see how to implement the upload of files, knowing the different existing variants in FastAPI. Chapter 6: In this chapter we will see how to connect a FastAPI application to a relational database such as MySQL. Chapter 7: In this chapter we will see installing and using a template engine in Python, specifically Jinja, with which we can return responses in HTML format. Chapter 8: In this chapter we will see installing and using a template engine in Python, specifically Jinja, with which we can return responses in HTML format. Chapter 9: In this chapter we will learn how to use dependencies. Chapter 10: In this chapter we will see how to use middleware to intercept requests to API methods and execute some procedure before the request or after generating the response. Chapter 11: In this chapter we will see how to create a user module, to register users, login, generate access tokens and logout. Chapter 12: In this chapter we will learn about some particularities and functionalities of FastAPI such as the use of annotations and the Ellipsis operator. Chapter 13: In this chapter we will see how to implement unit tests. Chapter 14: In this chapter we will know some general aspects applied to FastAPI.
Discover FastAPI features and best practices for building and deploying high-quality web APIs from scratch Key Features • A practical guide to developing production-ready web APIs rapidly in Python • Learn how to put FastAPI into practice by implementing it in real-world scenarios • Explore FastAPI, its syntax, and configurations for deploying applications Book Description RESTful web services are commonly used to create APIs for web-based applications owing to their light weight and high scalability. This book will show you how FastAPI, a high-performance web framework for building RESTful APIs in Python, allows you to build robust web APIs that are simple and intuitive and makes it easy to build quickly with very little boilerplate code. This book will help you set up a FastAPI application in no time and show you how to use FastAPI to build a REST API that receives and responds to user requests. You'll go on to learn how to handle routing and authentication while working with databases in a FastAPI application. The book walks you through the four key areas: building and using routes for create, read, update, and delete (CRUD) operations; connecting the application to SQL and NoSQL databases; securing the application built; and deploying your application locally or to a cloud environment. By the end of this book, you'll have developed a solid understanding of the FastAPI framework and be able to build and deploy robust REST APIs. What you will learn • Set up a FastAPI application that is fully functional and secure • Understand how to handle errors from requests and send proper responses in FastAPI • Integrate and connect your application to a SQL and NoSQL (MongoDB) database • Perform CRUD operations using SQL and FastAPI • Manage concurrency in FastAPI applications • Implement authentication in a FastAPI application • Deploy a FastAPI application to any platform Who this book is for This book is for Python developers who want to learn FastAPI in a pragmatic way to create robust web APIs with ease. If you are a Django or Flask developer looking to try something new that's faster, more efficient, and produces fewer bugs, this FastAPI Python book is for you. The book assumes intermediate-level knowledge of Python programming.
Wield the power of Python, React, and MongoDB to build web and data applications quickly and broaden your web development horizons Key FeaturesLearn how to build web applications without having to know the intricacies of the componentsBuild full stack projects without compromising on development speed and app performancePrepare yourself for the diverse world of web development, analytics, and data visualizationBook Description If you need to develop web applications quickly, where do you turn? Enter the FARM stack. The FARM stack combines the power of the Python ecosystem with REST and MongoDB and makes building web applications easy and fast. This book is a fast-paced, concise, and hands-on beginner's guide that will equip you with the skills you need to quickly build web applications by diving just deep enough into the intricacies of the stack's components. The book quickly introduces each element of the stack and then helps you merge them to build a medium-sized web application. You'll set up a document store with MongoDB, build a simple API with FastAPI, and create an application with React. Security is crucial on the web, so you'll learn about authentication and authorization with JSON Web Tokens. You'll also understand how to optimize images, cache responses with Redis, and add additional features to your application as well as explore tips, tricks, and best practices to make your development experience a breeze. Before you know it, you'll be deploying the application to different platforms. By the end of this book, you will have built a couple of functional applications efficiently and will have the springboard you need to delve into diverse and more specialized domains. What you will learnDiscover the flexibility of the FARM stackImplement complete JWT authentication with FastAPIExplore the various Python drivers for MongoDBDiscover the problems that React libraries solveBuild simple and medium web applications with the FARM stackDive into server-side rendering with Next.jsDeploy your app with Heroku, Vercel, Ubuntu Server and NetlifyUnderstand how to deploy and cache a FastAPI backendWho this book is for This book is for web developers and analysts who want to include the power of a modern asynchronous Python framework, a flexible data store and a powerful UI library with the combination of two of the most important programming languages today in their web development toolkit. Beginners in the field of information presentation will also find this book helpful. You must have a beginner-level understanding of Python, JavaScript, and HTML and CSS to get the most out of this book.
Boost your web developer potential and stay ahead in the fast-paced web development and AI race with the flexibility, adaptability, and robustness of the FARM stack Key Features Learn the basics of MongoDB to be able to model any type of data Explore the powerful Python web development ecosystem with Pydantic and FastAPI Future-proof your applications by integrating ChatGPT or other LLMs Purchase of the print or Kindle book includes a free PDF eBook Book Description Discover how to harness the power of the FARM stack—FastAPI, React, and MongoDB—to develop production-ready web applications of varying complexity. Written by a team of industry experts, including MongoDB champions and product leaders, this fast-paced, hands-on guide equips beginners with essential skills to build web applications efficiently. Introducing each element of the stack, the book demonstrates how to seamlessly integrate them to create a medium-sized web application. You'll set up MongoDB as a document store, construct a simple API with FastAPI, and build an application using React. The guide also covers enhancing application security through authentication and authorization with JSON Web Tokens. Beyond mastering the stack, you'll get to grips with integrating Large Language Models (like ChatGPT) for advanced functionality, such as automated email sending. Additionally, you'll learn how to make the most of Next.js 14, a robust full-stack framework offering improved developer experience. By the end of the book, you'll have created functional applications and gained the foundation to explore diverse and more specialized domains, expanding your development horizons. What you will learn Set up and manage MongoDB databases and collections, and model data Leverage the power of FastAPI to write complex APIs using pure Python Create frontends of varying complexity with the React library Build and deploy robust and secure backends using FastAPI and MongoDB Ship production-ready applications with Next.js 14, applying your React and backend knowledge Integrate Large Language Models, send emails, and do much more with the flexible FARM stack Who this book is for The book is for intermediate web developers with basic JavaScript and Python knowledge who want to enhance their developer skills, master a powerful and flexible stack, and write better applications faster.
Enhance your web development skills, from setting up your environment and advanced integrations to building robust, high-traffic web applications with practical, scalable solutions Key Features Explore FastAPI in depth, from basic setup to advanced features such as custom middleware and WebSockets Discover practical strategies to optimize app performance and handle high traffic Implement SQL and NoSQL integration techniques for versatile data management in FastAPI applications Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionFastAPI is a cutting-edge Python framework that is revolutionizing the way web apps and APIs are built. Known for its speed, simplicity, and scalability, FastAPI empowers developers to create high-performing applications with ease. This book will help you leverage FastAPI’s immense potential to handle high-traffic scenarios and integrate seamlessly with modern Python tools. The book begins by familiarizing you with the basics of setting up and configuring your FastAPI environment before moving to the intricacies of building RESTful APIs, managing data with SQL and NoSQL databases, and handling authentication and authorization. Next, you'll focus on advanced topics such as custom middleware, WebSocket communication, and integration with various Python libraries. Each chapter is meticulously crafted with practical recipes, progressing from foundational concepts to advanced features and best practices. The concluding chapters show you how to optimize performance, implement rate limiting, and execute background tasks, empowering you to become a proficient FastAPI developer. By the end of this book, you'll have gained the skills you need to migrate existing apps to FastAPI, and be equipped to tackle any challenge in the modern web development landscape, ensuring your apps are not only functional, but also efficient, secure, and scalable.What you will learn Explore advanced FastAPI functionalities such as dependency injection, custom middleware, and WebSockets Discover various types of data storage for powerful app functionality with SQL and NoSQL Implement testing and debugging practices for clean, robust code Integrate authentication and authorization mechanisms to secure web apps Acquire skills to seamlessly migrate existing applications to FastAPI Write unit and integration tests, ensuring reliability and security for your apps Deploy your FastAPI apps to production environments for real-world use Who this book is for This book is for Python developers looking to enhance their skills to build scalable, high-performance web apps using FastAPI. Professionals seeking practical guidance to create APIs and web apps that can handle significant traffic and scale as needed will also find this book helpful by learning from both foundational insights and advanced techniques. The book is also designed for anyone familiar with RESTful APIs, HTTP protocols, and database systems, as well as developers looking to migrate existing applications to FastAPI or explore its advanced features.
Get well-versed with FastAPI features and best practices for testing, monitoring, and deployment to run high-quality and robust data science applications Key FeaturesCover the concepts of the FastAPI framework, including aspects relating to asynchronous programming, type hinting, and dependency injectionDevelop efficient RESTful APIs for data science with modern PythonBuild, test, and deploy high performing data science and machine learning systems with FastAPIBook Description FastAPI is a web framework for building APIs with Python 3.6 and its later versions based on standard Python-type hints. With this book, you'll be able to create fast and reliable data science API backends using practical examples. This book starts with the basics of the FastAPI framework and associated modern Python programming language concepts. You'll be taken through all the aspects of the framework, including its powerful dependency injection system and how you can use it to communicate with databases, implement authentication and integrate machine learning models. Later, you'll cover best practices relating to testing and deployment to run a high-quality and robust application. You'll also be introduced to the extensive ecosystem of Python data science packages. As you progress, you'll learn how to build data science applications in Python using FastAPI. The book also demonstrates how to develop fast and efficient machine learning prediction backends and test them to achieve the best performance. Finally, you'll see how to implement a real-time face detection system using WebSockets and a web browser as a client. By the end of this FastAPI book, you'll have not only learned how to implement Python in data science projects but also how to maintain and design them to meet high programming standards with the help of FastAPI. What you will learnExplore the basics of modern Python and async I/O programmingGet to grips with basic and advanced concepts of the FastAPI frameworkImplement a FastAPI dependency to efficiently run a machine learning modelIntegrate a simple face detection algorithm in a FastAPI backendIntegrate common Python data science libraries in a web backendDeploy a performant and reliable web backend for a data science applicationWho this book is for This Python data science book is for data scientists and software developers interested in gaining knowledge of FastAPI and its ecosystem to build data science applications. Basic knowledge of data science and machine learning concepts and how to apply them in Python is recommended.
FastAPI is a young yet solid framework that takes advantage of newer Python features in a clean design. As its name implies, FastAPI is indeed fast, rivaling similar frameworks in languages such as Golang. With this practical book, developers familiar with Python will learn how FastAPI lets you accomplish more in less time with less code. Author Bill Lubanovic covers the nuts and bolts of FastAPI development with how-to guides on various topics such as forms, database access, graphics, maps, and more that will take you beyond the basics. This book also includes how-to guides that will get you up to speed on RESTful APIs, data validation, authorization, and performance. With its similarities to frameworks like Flask and Django, you'll find it easy to get started with FastAPI. Through the course of this book, you will: Learn how to build web applications with FastAPI Understand the differences between FastAPI, Starlette, and pydantic Learn two features that set FastAPI apart: asynchronous functions and data type checking and validation Examine new features of Python 3.8+, especially type annotations Understand the differences between sync and async Python Learn how to connect with external APIs and services
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This nine-volume set LNCS 14104 – 14112 constitutes the refereed workshop proceedings of the 23rd International Conference on Computational Science and Its Applications, ICCSA 2023, held at Athens, Greece, during July 3–6, 2023. The 350 full papers and 29 short papers and 2 PHD showcase papers included in this volume were carefully reviewed and selected from a total of 876 submissions. These nine-volumes includes the proceedings of the following workshops: Advances in Artificial Intelligence Learning Technologies: Blended Learning, STEM, Computational Thinking and Coding (AAILT 2023); Advanced Processes of Mathematics and Computing Models in Complex Computational Systems (ACMC 2023); Artificial Intelligence supported Medical data examination (AIM 2023); Advanced and Innovative web Apps (AIWA 2023); Assessing Urban Sustainability (ASUS 2023); Advanced Data Science Techniques with applications in Industry and Environmental Sustainability (ATELIERS 2023); Advances in Web Based Learning (AWBL 2023); Blockchain and Distributed Ledgers: Technologies and Applications (BDLTA 2023); Bio and Neuro inspired Computing and Applications (BIONCA 2023); Choices and Actions for Human Scale Cities: Decision Support Systems (CAHSC-DSS 2023); and Computational and Applied Mathematics (CAM 2023).
Essential Python libraries and frameworks that every aspiring data scientist, ML engineer, and Python developer should know. "Python is not just a language, it's a community where developers can learn, collaborate and create wonders." ~ Guido van Rossum (Creator of Python)